The pandemic was a period of change. Buying behaviours shifted as more people chose to shop online. Family units changed as people decided to add a pet to their home. And the pet food category changed as a result of all this, with many brands in the category showing a growth of up to 1.7% RSV and soaring ecommerce sales.

IAMS wanted to maximise their share of the category. But our research showed that pet owners were becoming overwhelmed by the number of brands competing for their attention. So, we needed to maximise the potential growth for IAMS without adding to the noise, which meant we shouldn’t simply try to outspend or out-shout our competition.

We set ourselves two challenges: find the audiences most likely to drive growth for IAMS and learn how to best persuade them to buy us. Data would be our key to achieving this.

Our data-driven profile of the Reynolds showed us their quirks; they wanted to be healthy, but were time poor, so needed quick fixes to make this possible; they believed themselves to be better placed to make decisions than health experts; they had money to spend, but value was important.

We knew lots about the Reynolds but we didn’t know which of those insights would help us change their behaviour. So, we launched an agile creative model, developing hypotheses on how to best use what we know about the Reynolds to personalise creative, measuring results to understand impact on brand perception and purchase behaviour.

We tested our personalised creative with a “Reynolds” beta community, identifying the insights and creatives that resonated and putting the sixteen top performers to market. We measured, learnt, and evolved creative find the most effective way to nudge our Reynolds to change their attitudes and behaviour.

First, we needed to find our audience. We started by honing in on shopper behaviour, analysing IRI data on 113,653 product purchases to uncover buying trends. We honed into dog food purchase specifically, developing a boolean logic and mapping data across two dimensions; volume of IAMS dry dog purchased and volume of competitor purchased. Through this analysis we identified our high potential growth audience: the Reynolds. Medium buyers of the category but not always buyers of IAMS. This was the audience we needed to reach.

Next, we personified the Reynolds, analysing over 11,000 attributes of the segment using our algorithmic people-based profiling tool, enriching this data with quant to understand their lives, motivations and attitudes to health, turning this into a data-driven pen portrait and a series of attributes to enable us to ‘find’ the Reynolds in the places and spaces they visit online.

Our personalised creative focuses on consideration and conversion driving activity, using OLV and programmatic banners to bring our hypotheses to life through creative tailored to what we’ve learnt about the Reynolds to date. Data drives creativity with results being analysed weekly and creative evolved based on media behaviours, brand lift and purchase intent; wider learnings being fed into mass-reach activity as well as our personalised assets.

Our tests to date have shown an increase in purchase intent; the Reynolds exposed to the campaign were 3X more likely to state that they would purchase IAMS than those in the control who saw non-personalised IAMS assets.

Response driving assets for Display have performed particularly highly, showing uplift +67% CTR against our benchmark. Most importantly, our modelling indicates that the continuation and expansion of this approach will likely drive incremental growth in sales for IAMS.